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Quantile Judgments of Lognormal Losses : An Experimental Investigation

The present study aims to investigate the quality of quantile judgments on a quantity of interest that follows the lognormal distribution, which is skewed and bounded from below with a long right tail. We conduct controlled experiments in which subjects predict the losses from a future typhoon based on losses from past typhoons. Our experiments find underconfidence of the 50% prediction intervals, which is primarily driven by overestimation of the 75th percentiles. We further perform exploratory analyses to disentangle sampling errors and judgmental biases in the overall miscalibration. Finally, we show that the correlations of log-transformed judgments between subjects are smaller than is justified by the information overlapping structure. It leads to overconfident aggregate predictions using the Bayes rule if we treat the low correlations as an indicator for independent information.

Ketersediaan

Informasi Detail

Judul Seri

DECISION ANALYSIS; Vol.18 No.1 March 2021

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 78 - 99

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

EXPERT ELICITATION
DEPENDENCE
QUANTILE ESTIMATES
SAMPLING ERRORS
JUDGEMENTAL BIASES

Info Detail Spesifik

https://doi.org/10.1287/deca.2020.0423

Pernyataan Tanggungjawab

Sulian Wang, Chen Wang

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